• Our solution follows a three-phase approach (Job/Data/Infra) with an added Visualization layer to display key metrics. The solution is designed to be cloud-agnostic.

• In the initial phase, the focus is on the Job Layer, utilizing Power BI as the front-end visualization tool on AWS. This phase will include setting up monitoring capabilities to track the performance and health of data jobs, such as ingestion, transformation, and loading processes.

• In the subsequent phases, we will extend the framework to integrate with Azure, ensuring cross-cloud compatibility. This will enable seamless data observability across both AWS and Azure environments. Further enhancements, achieved through cross-collaboration with co-Coe’s, will include the development of a custom UI and the integration of AI-Ops capabilities.

The Data Observability Dashboard provides real-time monitoring and insights into the health and performance of data systems and pipelines. It helps organizations track the flow, quality, and integrity of data across its lifecycle—from collection to transformation and storage. With visibility into potential issues, data anomalies, or failures, teams can address problems proactively to ensure the data used for decision-making, analytics, and operations is accurate, timely, and reliable.